Identifying named entities in queries and linking them to the corresponding entry in the knowledge base is known as the task of entity linking in queries (ELQ). Given a query q, return one or multiple interpretations of the query, each interpretation consists of a set of mention-entity pairs.

Entity retrieval is a core building block of semantic search. Given a search query, entity retrieval is the task of returning a ranked list of entities from an underlying knowledge base.

LTR-greedy: The recommended method (with respect to both efficiency and effectiveness) by Hasibi et al. [Hasibi et al., 2016], which employs a learning-to-rank model with various textual and semantic similarity features. Please note that the implemented method in Nordlys is slightly different from the one presented in [Hasibi et al., 2016] (i.e. the features and index). The corresponding files for this method are under data/el. Specifically: